MODIFIED NEURAL NETWORK-BASED STUDY INTO THE COEFFICIENT OF FRICTION IN PRESSED ASSEMBLIES.

The process of pressed assembly design is in a causal relation with the evaluation of friction coefficient. The evaluation of this parameter can be carried out by using various methods. In this paper, the algorithm for friction coefficient determination is analyzed. Analyses are based on roughness and hardness of tactile surfaces, with the implementation of a hybrid system based on neural networks. The value of this parameter is usually determined according to literature data. Many authors propose different values for this coefficient. In this case, the ratio between the minimum value and the maximum value is 1:17, and it depends on the designer’s decision. The implementation of neural networks results in the determination of friction coefficient and error in the range of 20%. [ABSTRACT FROM AUTHOR]